UB at CLEF 2005: Bilingual CLIR and Medical Image Retrieval Tasks
This paper presents the results of the State University of New York at Buffalo in the Cross Language Evaluation Forum 2005 (CLEF 2005). We participated in monolingual Portuguese, bilingual English-Portuguese and in the medical image retrieval tasks. We used the SMART retrieval system for text retrieval in the mono and bilingual retrieval tasks on Portuguese documents. The main goal of this part was to test formally the support for Portuguese that had been added to our system. Our results show an acceptable level of performance in the monolingual task. For the retrieval of medical images with multilingual annotations our main goal was to explore the combination of Content-Based Image Retrieval (CBIR) and text retrieval to retrieve medical images that have clinical annotations in English, French and German. We used a system that combines the content based image retrieval systems GIFT and the well known SMART system for text retrieval. Translation of English topics to French was performed by mapping the English text to UMLS concepts using MetaMap and the UMLS Metathesaurus. Our results on this task confirms that the combination of CBIR and text retrieval improves results significantly with respect to using either image or text retrieval alone.
KeywordsImage Retrieval Machine Translation Relevance Feedback Text Retrieval Pseudo Relevance Feedback
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